Charting the Landscape of Oxygen Ion Conductors: A 60-Year Dataset with Interpretable Regression Models

TL;DR

This paper presents a comprehensive 60-year dataset of oxygen ion conductors with corrected Arrhenius parameters and interpretable regression models, enabling systematic analysis and discovery of new materials.

Contribution

It provides a curated, corrected dataset of 483 materials and introduces interpretable regression models for understanding oxygen ion transport mechanisms.

Findings

Replotted conductivity data using correct Arrhenius equation

Identified local coordination and electrostatic interactions as key factors

Established a foundation for data-driven discovery of conductors

Abstract

Oxygen ion conductors are indispensable materials for such as solid oxide fuel cells, sensors, and membranes. Despite extensive research across diverse structural families, systematic data enabling comparative analysis remain scarce. Here, we present a curated dataset of oxygen ion conductors compiled from $84$ experimental reports spanning $60$ years, covering $483$ materials. Each record includes activation energy ($E_a$) and prefactor ($A$) derived from Arrhenius plots, alongside detailed metadata on structure, composition, measurement method, and data source. When the original papers derive these using an erroneous Arrhenius equation $\sigma_T=A\exp{\left(-\frac{E_a}{RT}\right)}$, where ($\sigma_T$ is the oxygen ion conductivity at temperature $T$ and $R$ is the gas constant), we replotted these using the correct one, $\sigma_{T}T=A\exp{\left(-\frac{E_a}{RT}\right)}$. To illustrate how the database can be used, we constructed interpretable regression models for predicting oxygen ionic conductivity. Two symbolic regression models for E_a and A suggest that oxygen ion transport is primarily governed by local coordination environment and the electrostatic interactions, respectively. This dataset establishes a reliable foundation for data-driven discovery and predictive modeling of next-generation oxygen ion conductors.